More work on AE7Q.
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@ -3,10 +3,13 @@
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# Use this file to scrape a series of dates from AE7Q
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# Set start and end date
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date_vec <- seq(as.Date("2024-07-23"), as.Date("2024-07-31"), by="days")
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date_vec <- seq(as.Date("2004-11-29"), as.Date("2024-07-22"), by="days")
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# Randomize dates we are querying
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date_vec <- sample(date_vec)
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dvbackup <- date_vec
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date_vec <- date_vec[1177:7176]
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ae7q_list <- list()
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for(i in 1:length(date_vec)){
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ae7q_new_url <- paste0("https://www.ae7q.com/query/list/ProcessDate.php?DATE=", date_vec[i])
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@ -23,14 +26,15 @@ for(i in 1:length(date_vec)){
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html_table()
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# Find the right table by the column names
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right_table_id <- grep(c("Callsign",
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"Region/ State",
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"Entity Name",
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"Applicant Type",
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"Licensee Class",
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"License Status",
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"Action Type"),
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lapply(ae7q_new_tables, names))
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right_table_id <- grep(paste(c("Callsign",
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"Region/ State",
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"Entity Name",
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"Applicant Type",
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"Licensee Class",
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"License Status",
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"Action Type"), collapse = " "),
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lapply(ae7q_new_tables, function(x) paste(names(x), collapse = " ")))
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ae7q_table_new <- ae7q_new_tables[[right_table_id]]
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@ -43,18 +47,18 @@ for(i in 1:length(date_vec)){
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relocate(date)
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} else {
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ae7q_list[[i]]<- data.frame("date" = date_vec[i],
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"Action Type" = NA,
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"count" = NA,
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"source" = "AE7Q",
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"source_detail" = ae7q_new_url)
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"Action Type" = NA,
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"count" = NA,
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"source" = "AE7Q",
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"source_detail" = ae7q_new_url)
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}
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# Wait for random time up to 10 seconds
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Sys.sleep(sample(1:10, 1))
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Sys.sleep(sample(1:5, 1))
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}
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# Combine all the data and sort by date
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a <- bind_rows(ae7q_list) %>%
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arrange(date)
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arrange(date)
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write.csv(a, "out/ae7q-actions-scraped.csv", row.names = F)
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